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Apache Mahout is an open source library that implements algorithms

spanning the "Three C's" (Collaborative Filtering, Clustering, and

Classification) of machine learning. When combined with Apache

Hadoop, Mahout can distribute its computations across a cluster of

servers. Its scalability and focus on real-world applications make

Mahout an increasingly popular choice for organizations seeking to

take advantage of large-scale machine learning. In this talk, Tom

Wheeler will introduce Apache Mahout and its capabilities, with

particular focus on how to use its collaborative filtering support to

handle the types of product recommendations that Steven Borrelli

described in the group's initial meeting.

Bio:

Tom Wheeler is a Senior Curriculum Developer at Cloudera, a company

that helps organizations derive value from their data through

products, consulting, training, certification, and support for Apache

Hadoop and related tools. Before joining Cloudera in 2011, he

developed engineering software for an aerospace company, helped to

design and implement a high-volume data processing system for a

healthcare company, and served as senior programmer/analyst for a

brokerage firm.

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